OpenRaiser/Intern-Atlas huggingface dataset:
Relay-assisted Multiple Access with Full-duplex Multi-Packet Reception
Venue: arXiv cs.IT 2015
Year: 2015

The effect of full-duplex cooperative relaying in a random access multiuser network is investigated here. First, we model the self-interference incurred due to full-duplex operation, assuming multi-packet reception capabilities for both the relay and the destination node. Traffic at the source nodes is considered saturated and the cooperative relay, which does not have packets of its own, stores a source packet that it receives successfully in its queue when the transmission to the destination has failed. We obtain analytical expressions for key performance metrics at the relay, such as arrival and service rates, stability conditions, and average queue length, as functions of the transmission probabilities, the self interference coefficient, and the links' outage probabilities. Furthermore, we study the impact of the relay node and the self-interference coefficient on the per-user and aggregate throughput, and the average delay per packet. We show that perfect self-interference cancelation plays a crucial role when the SINR threshold is small, since it may result to worse performance in throughput and delay comparing with the half-duplex case. This is because perfect self-interference cancelation can cause an unstable queue at the relay under some conditions.
Asynchronous Rumour Spreading in Social and Signed Topologies
Venue: arXiv cs.SI 2015
Year: 2015

In this paper, we present an experimental analysis of the asynchronous push & pull rumour spreading protocol. This protocol is, to date, the best-performing rumour spreading protocol for simple, scalable, and robust information dissemination in distributed systems. We analyse the effect that multiple parameters have on the protocol's performance, such as using memory to avoid contacting the same neighbor twice in a row, varying the stopping criteria used by nodes to decide when to stop spreading the rumour, employing more sophisticated neighbor selection policies instead of the standard uniform random choice, and others. Prior work has focused on either providing theoretical upper bounds regarding the number of rounds needed to spread the rumour to all nodes, or, proposes improvements by adjusting isolated parameters. To our knowledge, our work is the first to study how multiple parameters affect system behaviour both in isolation and combination and under a wide range of values. Our analysis is based on experimental simulations using real-world social network datasets, thus complementing prior theoretical work to shed light on how the protocol behaves in practical, real-world systems. We also study the behaviour of the protocol on a special type of social graph, called signed networks (e.g., Slashdot and Epinions), whose links indicate stronger trust relationships. Finally, through our detailed analysis, we demonstrate how a few simple additions to the protocol can improve the total time required to inform 100% of the nodes by a maximum of 99.69% and an average of 82.37%.
Relax but stay in control: from value to algorithms for online Markov decision processes
Venue: arXiv cs.LG 2015
Year: 2015

Online learning algorithms are designed to perform in non-stationary environments, but generally there is no notion of a dynamic state to model constraints on current and future actions as a function of past actions. State-based models are common in stochastic control settings, but commonly used frameworks such as Markov Decision Processes (MDPs) assume a known stationary environment. In recent years, there has been a growing interest in combining the above two frameworks and considering an MDP setting in which the cost function is allowed to change arbitrarily after each time step. However, most of the work in this area has been algorithmic: given a problem, one would develop an algorithm almost from scratch. Moreover, the presence of the state and the assumption of an arbitrarily varying environment complicate both the theoretical analysis and the development of computationally efficient methods. This paper describes a broad extension of the ideas proposed by Rakhlin et al. to give a general framework for deriving algorithms in an MDP setting with arbitrarily changing costs. This framework leads to a unifying view of existing methods and provides a general procedure for constructing new ones. Several new methods are presented, and one of them is shown to have important advantages over a similar method developed from scratch via an online version of approximate dynamic programming.
Wireless-Powered Relays in Cooperative Communications: Time-Switching Relaying Protocols and Throughput Analysis
Venue: arXiv cs.IT 2015
Year: 2015

We consider wireless-powered amplify-and-forward and decode-and-forward relaying in cooperative communications, where an energy constrained relay node first harvests energy through the received radio-frequency signal from the source and then uses the harvested energy to forward the source information to the destination node. We propose time-switching based energy harvesting (EH) and information transmission (IT) protocols with two modes of EH at the relay. For continuous time EH, the EH time can be any percentage of the total transmission block time. For discrete time EH, the whole transmission block is either used for EH or IT. The proposed protocols are attractive because they do not require channel state information at the transmitter side and enable relay transmission with preset fixed transmission power. We derive analytical expressions of the achievable throughput for the proposed protocols. The derived expressions are verified by comparison with simulations and allow the system performance to be determined as a function of the system parameters. Finally, we show that the proposed protocols outperform the existing fixed time duration EH protocols in the literature, since they intelligently track the level of the harvested energy to switch between EH and IT in an online fashion, allowing efficient use of resources.
Delaunay stability via perturbations
Venue: arXiv cs.CG 2015
Year: 2015

We present an algorithm that takes as input a finite point set in Euclidean space, and performs a perturbation that guarantees that the Delaunay triangulation of the resulting perturbed point set has quantifiable stability with respect to the metric and the point positions. There is also a guarantee on the quality of the simplices: they cannot be too flat. The algorithm provides an alternative tool to the weighting or refinement methods to remove poorly shaped simplices in Delaunay triangulations of arbitrary dimension, but in addition it provides a guarantee of stability for the resulting triangulation.
Reducing complexes in multidimensional persistent homology theory
Venue: arXiv cs.CG 2015
Year: 2015

The Discrete Morse Theory of Forman appeared to be useful for providing filtration-preserving reductions of complexes in the study of persistent homology. So far, the algorithms computing discrete Morse matchings have only been used for one-dimensional filtrations. This paper is perhaps the first attempt in the direction of extending such algorithms to multidimensional filtrations. Initial framework related to Morse matchings for the multidimensional setting is proposed, and a matching algorithm given by King, Knudson, and Mramor is extended in this direction. The correctness of the algorithm is proved, and its complexity analyzed. The algorithm is used for establishing a reduction of a simplicial complex to a smaller but not necessarily optimal cellular complex. First experiments with filtrations of triangular meshes are presented.
Look-Ahead Removal for Top-Down Tree Transducers
Venue: arXiv cs.FL 2015
Year: 2015

Top-down tree transducers are a convenient formalism for describing tree transformations. They can be equipped with regular look-ahead, which allows them to inspect a subtree before processing it. In certain cases, such a look-ahead can be avoided and the transformation can be realized by a transducer without look-ahead. Removing the look-ahead from a transducer, if possible, is technically highly challenging. For a restricted class of transducers with look-ahead, namely those that are total, deterministic, ultralinear, and bounded erasing, we present an algorithm that, for a given transducer from that class, (1) decides whether it is equivalent to a total deterministic transducer without look-ahead, and (2) constructs such a transducer if the answer is positive. For the whole class of total deterministic transducers with look-ahead we present a similar algorithm, which assumes that a so-called difference bound is known for the given transducer. The designer of a transducer can usually also determine a difference bound for it.
A Framework of Constructions of Minimal Storage Regenerating Codes with the Optimal Access/Update Property
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we present a generic framework for constructing systematic minimum storage regenerating codes with two parity nodes based on the invariant subspace technique. Codes constructed in our framework not only contain some best known codes as special cases, but also include some new codes with key properties such as the optimal access property and the optimal update property. In particular, for a given storage capacity of an individual node, one of the new codes has the largest number of systematic nodes and two of the new codes have the largest number of systematic nodes with the optimal update property.
Practical Inexact Proximal Quasi-Newton Method with Global Complexity Analysis
Venue: arXiv cs.LG 2015
Year: 2015

Recently several methods were proposed for sparse optimization which make careful use of second-order information [10, 28, 16, 3] to improve local convergence rates. These methods construct a composite quadratic approximation using Hessian information, optimize this approximation using a first-order method, such as coordinate descent and employ a line search to ensure sufficient descent. Here we propose a general framework, which includes slightly modified versions of existing algorithms and also a new algorithm, which uses limited memory BFGS Hessian approximations, and provide a novel global convergence rate analysis, which covers methods that solve subproblems via coordinate descent.
Parallel matrix factorization for low-rank tensor completion
Venue: arXiv cs.NA 2015
Year: 2015

Higher-order low-rank tensors naturally arise in many applications including hyperspectral data recovery, video inpainting, seismic data recon- struction, and so on. We propose a new model to recover a low-rank tensor by simultaneously performing low-rank matrix factorizations to the all-mode ma- tricizations of the underlying tensor. An alternating minimization algorithm is applied to solve the model, along with two adaptive rank-adjusting strategies when the exact rank is not known. Phase transition plots reveal that our algorithm can recover a variety of synthetic low-rank tensors from significantly fewer samples than the compared methods, which include a matrix completion method applied to tensor recovery and two state-of-the-art tensor completion methods. Further tests on real- world data show similar advantages. Although our model is non-convex, our algorithm performs consistently throughout the tests and give better results than the compared methods, some of which are based on convex models. In addition, the global convergence of our algorithm can be established in the sense that the gradient of Lagrangian function converges to zero.
Machine Learning Techniques for Intrusion Detection
Venue: arXiv cs.CR 2015
Year: 2015

An Intrusion Detection System (IDS) is a software that monitors a single or a network of computers for malicious activities (attacks) that are aimed at stealing or censoring information or corrupting network protocols. Most techniques used in today's IDS are not able to deal with the dynamic and complex nature of cyber attacks on computer networks. Hence, efficient adaptive methods like various techniques of machine learning can result in higher detection rates, lower false alarm rates and reasonable computation and communication costs. In this paper, we study several such schemes and compare their performance. We divide the schemes into methods based on classical artificial intelligence (AI) and methods based on computational intelligence (CI). We explain how various characteristics of CI techniques can be used to build efficient IDS.
Adaptive Protocols for Interactive Communication
Venue: arXiv cs.DS 2015
Year: 2015

How much adversarial noise can protocols for interactive communication tolerate? This question was examined by Braverman and Rao (IEEE Trans. Inf. Theory, 2014) for the case of "robust" protocols, where each party sends messages only in fixed and predetermined rounds. We consider a new class of non-robust protocols for Interactive Communication, which we call adaptive protocols. Such protocols adapt structurally to the noise induced by the channel in the sense that both the order of speaking, and the length of the protocol may vary depending on observed noise. We define models that capture adaptive protocols and study upper and lower bounds on the permissible noise rate in these models. When the length of the protocol may adaptively change according to the noise, we demonstrate a protocol that tolerates noise rates up to $1/3$. When the order of speaking may adaptively change as well, we demonstrate a protocol that tolerates noise rates up to $2/3$. Hence, adaptivity circumvents an impossibility result of $1/4$ on the fraction of tolerable noise (Braverman and Rao, 2014).
Seeking Anonymity in an Internet Panopticon
Venue: arXiv cs.CR 2015
Year: 2015

Obtaining and maintaining anonymity on the Internet is challenging. The state of the art in deployed tools, such as Tor, uses onion routing (OR) to relay encrypted connections on a detour passing through randomly chosen relays scattered around the Internet. Unfortunately, OR is known to be vulnerable at least in principle to several classes of attacks for which no solution is known or believed to be forthcoming soon. Current approaches to anonymity also appear unable to offer accurate, principled measurement of the level or quality of anonymity a user might obtain. Toward this end, we offer a high-level view of the Dissent project, the first systematic effort to build a practical anonymity system based purely on foundations that offer measurable and formally provable anonymity properties. Dissent builds on two key pre-existing primitives - verifiable shuffles and dining cryptographers - but for the first time shows how to scale such techniques to offer measurable anonymity guarantees to thousands of participants. Further, Dissent represents the first anonymity system designed from the ground up to incorporate some systematic countermeasure for each of the major classes of known vulnerabilities in existing approaches, including global traffic analysis, active attacks, and intersection attacks. Finally, because no anonymity protocol alone can address risks such as software exploits or accidental self-identification, we introduce WiNon, an experimental operating system architecture to harden the uses of anonymity tools such as Tor and Dissent against such attacks.
Path Finding I :Solving Linear Programs with Õ(sqrt(rank)) Linear System Solves
Venue: arXiv cs.DS 2015
Year: 2015

In this paper we present a new algorithm for solving linear programs that requires only $\tilde{O}(\sqrt{rank(A)}L)$ iterations to solve a linear program with $m$ constraints, $n$ variables, and constraint matrix $A$, and bit complexity $L$. Each iteration of our method consists of solving $\tilde{O}(1)$ linear systems and additional nearly linear time computation. Our method improves upon the previous best iteration bound by factor of $\tildeΩ((m/rank(A))^{1/4})$ for methods with polynomial time computable iterations and by $\tildeΩ((m/rank(A))^{1/2})$ for methods which solve at most $\tilde{O}(1)$ linear systems in each iteration. Our method is parallelizable and amenable to linear algebraic techniques for accelerating the linear system solver. As such, up to polylogarithmic factors we either match or improve upon the best previous running times in both depth and work for different ratios of $m$ and $rank(A)$. Moreover, our method matches up to polylogarithmic factors a theoretical limit established by Nesterov and Nemirovski in 1994 regarding the use of a "universal barrier" for interior point methods, thereby resolving a long-standing open question regarding the running time of polynomial time interior point methods for linear programming.
On Decentralized Estimation with Active Queries
Venue: arXiv cs.MA 2015
Year: 2015

We consider the problem of decentralized 20 questions with noise for multiple players/agents under the minimum entropy criterion in the setting of stochastic search over a parameter space, with application to target localization. We propose decentralized extensions of the active query-based stochastic search strategy that combines elements from the 20 questions approach and social learning. We prove convergence to correct consensus on the value of the parameter. This framework provides a flexible and tractable mathematical model for decentralized parameter estimation systems based on active querying. We illustrate the effectiveness and robustness of the proposed decentralized collaborative 20 questions algorithm for random network topologies with information sharing.
A Parallel Space Saving Algorithm For Frequent Items and the Hurwitz zeta distribution
Venue: arXiv cs.DS 2015
Year: 2015

We present a message-passing based parallel version of the Space Saving algorithm designed to solve the $k$--majority problem. The algorithm determines in parallel frequent items, i.e., those whose frequency is greater than a given threshold, and is therefore useful for iceberg queries and many other different contexts. We apply our algorithm to the detection of frequent items in both real and synthetic datasets whose probability distribution functions are a Hurwitz and a Zipf distribution respectively. Also, we compare its parallel performances and accuracy against a parallel algorithm recently proposed for merging summaries derived by the Space Saving or Frequent algorithms.
Coded Slotted ALOHA: A Graph-Based Method for Uncoordinated Multiple Access
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, a random access scheme is introduced which relies on the combination of packet erasure correcting codes and successive interference cancellation (SIC). The scheme is named coded slotted ALOHA. A bipartite graph representation of the SIC process, resembling iterative decoding of generalized low-density parity-check codes over the erasure channel, is exploited to optimize the selection probabilities of the component erasure correcting codes via density evolution analysis. The capacity (in packets per slot) of the scheme is then analyzed in the context of the collision channel without feedback. Moreover, a capacity bound is developed and component code distributions tightly approaching the bound are derived.
Asymmetric Compute-and-Forward with CSIT
Venue: arXiv cs.IT 2015
Year: 2015

We present a modified compute-and-forward scheme which utilizes Channel State Information at the Transmitters (CSIT) in a natural way. The modified scheme allows different users to have different coding rates, and use CSIT to achieve larger rate region. This idea is applicable to all systems which use the compute-and-forward technique and can be arbitrarily better than the regular scheme in some settings.
A Multicast Approach for Constructive Interference Precoding in MISO Downlink Channel
Venue: arXiv cs.IT 2015
Year: 2015

This paper studies the concept of jointly utilizing the data information(DI)and channel state information (CSI) in order to design symbol-level precoders for a multiple input and single output (MISO) downlink channel. In this direction, the interference among the simultaneous data streams is transformed to useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. We propose a maximum ratio transmissions (MRT) based algorithm that jointly exploits DI and CSI to gain the benefits from these useful signals. In this context, a novel framework to minimize the power consumption is proposed by formalizing the duality between the constructive interference downlink channel and the multicast channels. The numerical results have shown that the proposed schemes outperform other state of the art techniques.
How to Walk Your Dog in the Mountains with No Magic Leash
Venue: arXiv cs.CG 2015
Year: 2015

We describe a $O(\log n )$-approximation algorithm for computing the homotopic \Frechet distance between two polygonal curves that lie on the boundary of a triangulated topological disk. Prior to this work, algorithms were known only for curves on the Euclidean plane with polygonal obstacles. A key technical ingredient in our analysis is a $O(\log n)$-approximation algorithm for computing the minimum height of a homotopy between two curves. No algorithms were previously known for approximating this parameter. Surprisingly, it is not even known if computing either the homotopic \Frechet distance, or the minimum height of a homotopy, is in NP.
Minimizing Flow-Time on Unrelated Machines
Venue: arXiv cs.DS 2015
Year: 2015

We consider some flow-time minimization problems in the unrelated machines setting. In this setting, there is a set of $m$ machines and a set of $n$ jobs, and each job $j$ has a machine dependent processing time of $p_{ij}$ on machine $i$. The flow-time of a job is the total time the job spends in the system (completion time minus its arrival time), and is one of the most natural quality of service measure. We show the following two results: an $O(\min(\log^2 n,\log n \log P))$ approximation algorithm for minimizing the total-flow time, and an $O(\log n)$ approximation for minimizing the maximum flow-time. Here $P$ is the ratio of maximum to minimum job size. These are the first known poly-logarithmic guarantees for both the problems.
Equilibrium Points of an AND-OR Tree: under Constraints on Probability
Venue: arXiv cs.AI 2015
Year: 2015

We study a probability distribution d on the truth assignments to a uniform binary AND-OR tree. Liu and Tanaka [2007, Inform. Process. Lett.] showed the following: If d achieves the equilibrium among independent distributions (ID) then d is an independent identical distribution (IID). We show a stronger form of the above result. Given a real number r such that 0 < r < 1, we consider a constraint that the probability of the root node having the value 0 is r. Our main result is the following: When we restrict ourselves to IDs satisfying this constraint, the above result of Liu and Tanaka still holds. The proof employs clever tricks of induction. In particular, we show two fundamental relationships between expected cost and probability in an IID on an OR-AND tree: (1) The ratio of the cost to the probability (of the root having the value 0) is a decreasing function of the probability x of the leaf. (2) The ratio of derivative of the cost to the derivative of the probability is a decreasing function of x, too.
More ties than we thought
Venue: arXiv cs.FL 2015
Year: 2015

We extend the existing enumeration of neck tie-knots to include tie-knots with a textured front, tied with the narrow end of a tie. These tie-knots have gained popularity in recent years, based on reconstructions of a costume detail from The Matrix Reloaded, and are explicitly ruled out in the enumeration by Fink and Mao (2000). We show that the relaxed tie-knot description language that comprehensively describes these extended tie-knot classes is context free. It has a regular sub-language that covers all the knots that originally inspired the work. From the full language, we enumerate 266 682 distinct tie-knots that seem tie-able with a normal neck-tie. Out of these 266 682, we also enumerate 24 882 tie-knots that belong to the regular sub-language.